Paralyzed Woman Moves Thought Controlled Robotic Arm With Immense Precision

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Justine Alford

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293 Paralyzed Woman Moves Thought Controlled Robotic Arm With Immense Precision
Wodlinger et al., Journal of Neural Engineering 2015

Over the last few years there have been some incredible technological developments that are offering new hope for paralyzed patients. Electrical stimulation and nerve cell transplants have enabled individuals to regain movement in their legs, and even allowed them to stand or walk with a frame. Brain implants have allowed quadriplegic patients to move their fingers and hands for the first time in years using their minds. And now, scientists have developed a system that has allowed a paralyzed woman to control a robotic arm with immense precision, using only her thoughts. 

Jan Scheuermann is a 55-year-old woman with a neurodegenerative disease that has left her paralyzed from the neck down since 2003. Back in 2012, she took part in a trial conducted by scientists at the University of Pittsburgh who had been working on an innovative brain-machine interface system.


They implanted two microelectrode grids, just four millimeters in size, in a particular spot of the left motor cortex that is responsible for controlling movement of her right arm and hand. The grid contains 96 tiny contact points, each of which pick up firing signals from an individual neuron. These devices were then hooked up to a computer, which recorded and analyzed brain activity within this region.

Next, the team asked Scheuermann to think about moving her arm and hand, and then used complex computer algorithms to marry up the patterns of electrical activity within her brain to her thoughts about specific movements. These patterns were then translated by the system into the appropriate movements, allowing Scheuermann to control a robotic arm with just her mind. Not only could she move the arm with impressive fluidity, but she could also pick up a variety of objects, with a 91.6% success rate. Impressively, she even managed to use the arm to feed herself a bar of chocolate.

Now, the team has developed the system even further, allowing a remarkable level of control. As described in the Journal of Neural Engineering, the updated algorithm can now detect four new control signals related to hand shape. This means that users can scoop, extend the thumb and pinch, allowing patients to move the arm in a total of 10 different ways. As shown in the video below, Scheuermann is now able to control the prosthetic with remarkable precision, using it to pick up and move a variety of objects.



The system isn’t ready for widespread use yet, and still requires a bit more tweaking. However, they are hopeful that once the technology moves out of the lab, the range of movements achievable by the prosthetic will help paralyzed patients regain a certain degree of independence, if they can be trained to successfully control it.

[Via University of PittsburghNew Scientist, PopSci and Journal of Neural Engineering]